Biomimetics

25 pages, 9712 KiB

Open AccessArticle

Development of a Dragonfly-Inspired High Aerodynamic Force Flapping-Wing Mechanism Using Asymmetric Wing Flapping Motion

by Jinze Liang, Mengzong Zheng, Tianyu Pan, Guanting Su, Yuanjun Deng, Mengda Cao and Qiushi Li

Biomimetics 2025, 10(5), 309; https://doi.org/10.3390/biomimetics10050309 (registering DOI) - 11 May 2025

Abstract

Bionic micro air vehicles are currently being popularized for military as well as civilian use and dragonflies display a wealth of skill in their remarkable flight capabilities. This study designs an asymmetric motion flapping-wing mechanism inspired by the dragonfly, using a single actuator [...] Read more.

Bionic micro air vehicles are currently being popularized for military as well as civilian use and dragonflies display a wealth of skill in their remarkable flight capabilities. This study designs an asymmetric motion flapping-wing mechanism inspired by the dragonfly, using a single actuator to achieve the coupling of stroke and pitch motion. This study simulates the motion of the dragonfly’s wings using the designed mechanism and experimentally validates the motion laws and aerodynamic characteristics of the mechanism. The analysis focuses on the asymmetry in the wing’s stroke and pitch motion and their aerodynamic implications. The flapping-wing mechanism accurately replicates the wing motion of a real dragonfly in flight, and the maximum lift-to-weight ratio can reach up to 230.2%, demonstrating significant aerodynamic benefits. This mechanism provides valuable guidance for the structural design and kinematic control of future flapping-wing vehicles. Full article

(This article belongs to the Special Issue Bioinspired Engineered Systems)

► Show Figures

Figure 1

19 pages, 1438 KiB

Open AccessArticle

µ-Raman Spectroscopic Temperature Dependence Study of Biomimetic Lipid 1,2-Diphytanoyl-sn-glycero-3-phosphocholine

by Carmen Rizzuto, Antonello Nucera, Irene Barba Castagnaro, Riccardo C. Barberi and Marco Castriota

Biomimetics 2025, 10(5), 308; https://doi.org/10.3390/biomimetics10050308 (registering DOI) - 11 May 2025

Abstract

Raman spectroscopy is one of the best techniques for obtaining information concerning the physical–chemical interactions between a lipid and a solvent. Phospholipids in water are the main elements of cell membranes and, by means of their chemical and physical structures, their cells can [...] Read more.

Raman spectroscopy is one of the best techniques for obtaining information concerning the physical–chemical interactions between a lipid and a solvent. Phospholipids in water are the main elements of cell membranes and, by means of their chemical and physical structures, their cells can interact with other biological molecules (i.e., proteins and vitamins) and express their own biological functions. Phospholipids, due to their amphiphilic structure, form biomimetic membranes which are useful for studying cellular interactions and drug delivery. Synthetic systems such as DPhPC-based liposomes replicate the key properties of biological membranes. Among the different models, phospholipid mimetic membrane models of lamellar vesicles have been greatly supported. In this work, a biomimetic system, a deuterium solution (50 mM) of the synthetic phospholipid 1,2-diphytanoyl-sn-glycero-3-phosphocholine (DPhDC), is studied using μ-Raman spectroscopy in a wide temperature range from −181.15 °C up to 22.15 °C, including the following temperatures: −181.15 °C, −146.15 °C, −111.15 °C, −76.15 °C, −61.15 °C, −46.15 °C, −31.15 °C, −16.15 °C, −1.15 °C, 14.15 °C, and 22.15 °C. Based on the Raman evidence, phase transitions as a function of temperature are shown and grouped into five classes, where the corresponding Raman modes describe the stretching of the (C−N) bond in the choline head group (gauche) and the asymmetric stretching of the (O−P−O) bond. The acquisition temperature of each Raman spectrum characterizes the rocking mode of the methylene of the acyl chain. These findings enhance our understanding of the role of artificial biomimetic lipids in complex phospholipid membranes and provide valuable insights for optimizing their use in biosensing applications. Although the phase stability of DPhPC is known, the collected Raman data suggest subtle molecular rearrangements, possibly due to hydration and second-order transitions, which are relevant for membrane modeling and biosensing applications. Full article

► Show Figures

Figure 1

14 pages, 2535 KiB

Open AccessArticle

Can Anthropomorphic Interfaces Improve the Ergonomics and Safety Performance of Human–Machine Collaboration in Multitasking Scenarios?—An Example of Human–Machine Co-Driving in High-Speed Trains

by Yunan Jiang and Jinyi Zhi

Biomimetics 2025, 10(5), 307; https://doi.org/10.3390/biomimetics10050307 (registering DOI) - 11 May 2025

Abstract

High-speed trains are some of the most important transportation vehicles requiring human–computer collaboration. This study investigated the effects of different types of icons on recognition performance and cognitive load during frequent observation and sudden takeover tasks in high-speed trains. The results of this [...] Read more.

High-speed trains are some of the most important transportation vehicles requiring human–computer collaboration. This study investigated the effects of different types of icons on recognition performance and cognitive load during frequent observation and sudden takeover tasks in high-speed trains. The results of this study can be used to improve the efficiency of human–computer collaboration tasks and driving safety. In this study, 48 participants were selected for a simulated driving experiment on a high-speed train. The recognition reaction time, operation completion time, number of recognition errors, number of operation errors, SUS scale, and NASA-TLX questionnaire for the icons were all analyzed using analysis of variance (ANOVA) and the nonparametric Mann–Whitney U test. The results show that anthropomorphic icons can reduce the drivers’ visual fatigue and mental load in frequent observation tasks due to the anthropomorphic facial features attracting driver attention through simple lines and improving visual search efficiency. However, for the sudden takeover human–computer collaboration task, the facial features of the anthropomorphic icons were not recognized in a short period of time. Additionally, due to the positive emotions produced by the facial features, the drivers did not perceive the suddenness and danger of the sudden takeover human–computer collaboration task, resulting in the traditional icons being more capable of arousing the drivers’ alertness and helping them take over the task quickly. At the same time, neither type of icon triggered misrecognition or operation for sufficiently skilled drivers. These research results can provide guidance for the design of icons in human–computer collaborative interfaces for different types of driving tasks in high-speed trains, which can help improve the recognition speed, reaction speed, and safety of drivers. Full article

(This article belongs to the Special Issue Intelligent Human–Robot Interaction: 3rd Edition)

► Show Figures

Figure 1

16 pages, 12995 KiB

Open AccessArticle

DEM Study and Field Experiments on Coupling Bionic Subsoilers

by Zihe Xu, Hongyan Qi, Lidong Wang, Shuo Wang, Xuanting Liu and Yunhai Ma

Biomimetics 2025, 10(5), 306; https://doi.org/10.3390/biomimetics10050306 (registering DOI) - 11 May 2025

Abstract

Subsoiling is an effective tillage method for breaking up the plough pan and reducing soil bulk density. However, subsoilers often encounter challenges such as high draft resistance and excessive energy consumption during operation. In this study, the claw toes of the badger and [...] Read more.

Subsoiling is an effective tillage method for breaking up the plough pan and reducing soil bulk density. However, subsoilers often encounter challenges such as high draft resistance and excessive energy consumption during operation. In this study, the claw toes of the badger and the scales of the pangolin were selected as bionic prototypes, based on which coupling bionic subsoilers were designed. The discrete element method (DEM) was used to simulate and analyze the interactions between soil and both the standard subsoiler and coupling bionic subsoilers. Field experiments were conducted to validate the simulation results. The simulation results showed that the coupling bionic subsoilers reduced the draft force by 7.70–16.02% compared to the standard subsoiler at different working speeds. Additionally, the soil disturbance coefficient of the coupling bionic subsoilers decreased by 5.91–13.57%, and the soil bulkiness was reduced by 2.84–18.41%. The field experiment results showed that coupling bionic subsoilers reduced the average draft force by 11.06% and decreased the soil disturbance area. The field experiments validated the accuracy of DEM simulation results. This study provides valuable insights for designing more efficient subsoilers. Full article

(This article belongs to the Special Issue Drag Reduction through Bionic Approaches)

► Show Figures

Figure 1

19 pages, 7462 KiB

Open AccessArticle

A Bionic Goal-Oriented Path Planning Method Based on an Experience Map

by Qiang Zou and Yiwei Chen

Biomimetics 2025, 10(5), 305; https://doi.org/10.3390/biomimetics10050305 (registering DOI) - 11 May 2025

Abstract

Brain-inspired bionic navigation is a groundbreaking technological approach that emulates the biological navigation systems found in mammalian brains. This innovative method leverages experiences within cognitive space to plan global paths to targets, showcasing remarkable autonomy and adaptability to various environments. This work introduces [...] Read more.

Brain-inspired bionic navigation is a groundbreaking technological approach that emulates the biological navigation systems found in mammalian brains. This innovative method leverages experiences within cognitive space to plan global paths to targets, showcasing remarkable autonomy and adaptability to various environments. This work introduces a novel bionic, goal-oriented path planning approach for mobile robots. First, an experience map is constructed using NeuroSLAM, a bio-inspired simultaneous localization and mapping method. Based on this experience map, a successor representation model is then developed through reinforcement learning, and a goal-oriented predictive map is formulated to address long-term reward estimation challenges. By integrating goal-oriented rewards, the proposed algorithm efficiently plans optimal global paths in complex environments for mobile robots. Our experimental validation demonstrates the method’s effectiveness in experience sequence prediction and goal-oriented global path planning. The comparative results highlight its superior performance over traditional Dijkstra’s algorithm, particularly in terms of adaptability to environmental changes and computational efficiency in optimal global path generation. Full article

(This article belongs to the Special Issue Bio-Inspired Robotics and Applications 2025)

14 pages, 5866 KiB

Open AccessArticle

Core-Sheath Structured Yarn for Biomechanical Sensing in Health Monitoring

by Wenjing Fan, Cheng Li, Bingping Yu, Te Liang, Junrui Li, Dapeng Wei and Keyu Meng

Biomimetics 2025, 10(5), 304; https://doi.org/10.3390/biomimetics10050304 - 9 May 2025

Abstract

The rapidly evolving field of functional yarns has garnered substantial research attention due to their exceptional potential in enabling next-generation electronic textiles for wearable health monitoring, human–machine interfaces, and soft robotics. Despite notable advancements, the development of yarn-based strain sensors that simultaneously achieve [...] Read more.

The rapidly evolving field of functional yarns has garnered substantial research attention due to their exceptional potential in enabling next-generation electronic textiles for wearable health monitoring, human–machine interfaces, and soft robotics. Despite notable advancements, the development of yarn-based strain sensors that simultaneously achieve high flexibility, stretchability, superior comfort, extended operational stability, and exceptional electrical performance remains a critical challenge, hindered by material limitations and structural design constraints. Here, we present a bioinspired, hierarchically structured core-sheath yarn sensor (CSSYS) engineered through an efficient dip-coating process, which synergistically integrates the two-dimensional conductive MXene nanosheets and one-dimensional silver nanowires (AgNWs). Furthermore, the sensor is encapsulated using a yarn-based protective layer, which not only preserves its inherent flexibility and wearability but also effectively mitigates oxidative degradation of the sensitive materials, thereby significantly enhancing long-term durability. Drawing inspiration from the natural architecture of plant stems—where the inner core provides structural integrity while a flexible outer sheath ensures adaptive protection—the CSSYS exhibits outstanding mechanical and electrical performance, including an ultralow strain detection limit (0.05%), an ultrahigh gauge factor (up to 744.45), rapid response kinetics (80 ms), a broad sensing range (0–230% strain), and exceptional cyclic stability (>20,000 cycles). These remarkable characteristics enable the CSSYS to precisely capture a broad spectrum of physiological signals, ranging from subtle arterial pulsations and respiratory rhythms to large-scale joint movements, demonstrating its immense potential for next-generation wearable health monitoring systems. Full article

(This article belongs to the Special Issue Bio-Inspired Flexible Sensors)

► Show Figures

Graphical abstract

35 pages, 3603 KiB

Open AccessArticle

ADVCSO: Adaptive Dynamically Enhanced Variant of Chicken Swarm Optimization for Combinatorial Optimization Problems

by Kunwei Wu, Liangshun Wang and Mingming Liu

Biomimetics 2025, 10(5), 303; https://doi.org/10.3390/biomimetics10050303 - 9 May 2025

Abstract

High-dimensional complex optimization problems are pervasive in engineering and scientific computing, yet conventional algorithms struggle to meet collaborative optimization requirements due to computational complexity. While Chicken Swarm Optimization (CSO) demonstrates an intuitive understanding and straightforward implementation for low-dimensional problems, it suffers from limitations [...] Read more.

High-dimensional complex optimization problems are pervasive in engineering and scientific computing, yet conventional algorithms struggle to meet collaborative optimization requirements due to computational complexity. While Chicken Swarm Optimization (CSO) demonstrates an intuitive understanding and straightforward implementation for low-dimensional problems, it suffers from limitations including a low convergence precision, uneven initial solution distribution, and premature convergence. This study proposes an Adaptive Dynamically Enhanced Variant of Chicken Swarm Optimization (ADVCSO) algorithm. First, to address the uneven initial solution distribution in the original algorithm, we design an elite perturbation initialization strategy based on good point sets, combining low-discrepancy sequences with Gaussian perturbations to significantly improve the search space coverage. Second, targeting the exploration–exploitation imbalance caused by fixed role proportions, a dynamic role allocation mechanism is developed, integrating cosine annealing strategies to adaptively regulate flock proportions and update cycles, thereby enhancing exploration efficiency. Finally, to mitigate the premature convergence induced by single update rules, hybrid mutation strategies are introduced through phased mutation operators and elite dimension inheritance mechanisms, effectively reducing premature convergence risks. Experiments demonstrate that the ADVCSO significantly outperforms state-of-the-art algorithms on 27 of 29 CEC2017 benchmark functions, achieving a 2–3 orders of magnitude improvement in convergence precision over basic CSO. In complex composite scenarios, its convergence accuracy approaches that of the championship algorithm JADE within a 10⁻² magnitude difference. For collaborative multi-subproblem optimization, the ADVCSO exhibits a superior performance in both Multiple Traveling Salesman Problems (MTSPs) and Multiple Knapsack Problems (MKPs), reducing the maximum path length in MTSPs by 6.0% to 358.27 units while enhancing the MKP optimal solution success rate by 62.5%. The proposed algorithm demonstrates an exceptional performance in combinatorial optimization and holds a significant engineering application value. Full article

(This article belongs to the Special Issue Exploration of Bio-Inspired Computing)

32 pages, 4186 KiB

Open AccessArticle

Comprehensive Adaptive Enterprise Optimization Algorithm and Its Engineering Applications

by Shuxin Wang, Yejun Zheng, Li Cao and Mengji Xiong

Biomimetics 2025, 10(5), 302; https://doi.org/10.3390/biomimetics10050302 - 9 May 2025

Abstract

In this study, a brand-new algorithm called the Comprehensive Adaptive Enterprise Development Optimizer (CAED) is proposed to overcome the drawbacks of the Enterprise Development (ED) algorithm in complex optimization tasks. In particular, it aims to tackle the problems of slow convergence and low [...] Read more.

In this study, a brand-new algorithm called the Comprehensive Adaptive Enterprise Development Optimizer (CAED) is proposed to overcome the drawbacks of the Enterprise Development (ED) algorithm in complex optimization tasks. In particular, it aims to tackle the problems of slow convergence and low precision. To enhance the algorithm’s ability to break free from local optima, a lens imaging reverse learning approach is incorporated. This approach creates reverse solutions by utilizing the concepts of optical imaging. As a result, it expands the search range and boosts the probability of finding superior solutions beyond local optima. Moreover, an environmental sensitivity-driven adaptive inertial weight approach is developed. This approach dynamically modifies the equilibrium between global exploration, which enables the algorithm to search for new promising areas in the solution space, and local development, which is centered on refining the solutions close to the currently best-found areas. To evaluate the efficacy of the CAED, 23 benchmark functions from CEC2005 are chosen for testing. The performance of the CAED is contrasted with that of nine other algorithms, such as the Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), and the Antlion Optimizer (AOA). Experimental findings show that for unimodal functions, the standard deviation of the CAED is almost 0, which reflects its high accuracy and stability. In the case of multimodal functions, the optimal value obtained by the CAED is notably better than those of other algorithms, further emphasizing its outstanding performance. The CAED algorithm is also applied to engineering optimization challenges, like the design of cantilever beams and three-bar trusses. For the cantilever beam problem, the optimal solution achieved by the CAED is 13.3925, with a standard deviation of merely 0.0098. For the three-bar truss problem, the optimal solution is 259.805047, and the standard deviation is an extremely small 1.11 × 10⁻⁷. These results are much better than those achieved by the traditional ED algorithm and the other comparative algorithms. Overall, through the coordinated implementation of multiple optimization strategies, the CAED algorithm exhibits high precision, strong robustness, and rapid convergence when searching in complex solution spaces. As such, it offers an efficient approach for solving various engineering optimization problems. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 3rd Edition)

► Show Figures

Figure 1

25 pages, 58458 KiB

Open AccessArticle

Design, Modeling, and Experimental Validation of a Bio-Inspired Rigid–Flexible Continuum Robot Driven by Flexible Shaft Tension–Torsion Synergy

by Jiaxiang Dong, Quanquan Liu, Peng Li, Chunbao Wang, Xuezhi Zhao and Xiping Hu

Biomimetics 2025, 10(5), 301; https://doi.org/10.3390/biomimetics10050301 - 8 May 2025

Abstract

This paper presents a bio-inspired rigid–flexible continuum robot driven by flexible shaft tension–torsion synergy, tackling the trade-off between actuation complexity and flexibility in continuum robots. Inspired by the muscular arrangement of octopus arms, enabling versatile multi-degree-of-freedom (DoF) movements, the robot achieves 6-DoF motion [...] Read more.

This paper presents a bio-inspired rigid–flexible continuum robot driven by flexible shaft tension–torsion synergy, tackling the trade-off between actuation complexity and flexibility in continuum robots. Inspired by the muscular arrangement of octopus arms, enabling versatile multi-degree-of-freedom (DoF) movements, the robot achieves 6-DoF motion and 1-DoF gripper opening and closing movement with only six flexible shafts, simplifying actuation while boosting dexterity. A comprehensive kinetostatic model, grounded in Cosserat rod theory, is developed; this model explicitly incorporates the coupling between the spinal rods and flexible shafts, the distributed gravitational effects of spacer disks, and friction within the guide tubes. Experimental validation using a physical prototype reveals that accounting for spacer disk gravity diminishes the maximum shape prediction error from 20.56% to 0.60% relative to the robot’s total length. Furthermore, shape perception experiments under no-load and 200 g load conditions show average errors of less than 2.01% and 2.61%, respectively. Performance assessments of the distal rigid joint showcased significant dexterity, including a 53

^{\circ}

grasping range, 360

^{\circ}

continuous rotation, and a pitching range from −40

^{\circ}

to +45

^{\circ}

. Successful obstacle avoidance and long-distance target reaching experiments further demonstrate the robot’s effectiveness, highlighting its potential for applications in medical and industrial fields. Full article

(This article belongs to the Special Issue Biologically Inspired Design and Control of Robots: Second Edition)

16 pages, 8582 KiB

Open AccessArticle

A Biomimetic Flapping Mechanism for Insect Robots Driven by Indirect Flight Muscles

by Yuma Shiokawa, Renke Liu and Hideyuki Sawada

Biomimetics 2025, 10(5), 300; https://doi.org/10.3390/biomimetics10050300 - 8 May 2025

Abstract

Insect flight mechanisms are highly efficient and involve complex hinge structures that facilitate amplified wing movement through thoracic deformation. However, in the field of flapping-wing robots, the replication of thoracic skeletal structures has received little attention. In this study, we propose and compare [...] Read more.

Insect flight mechanisms are highly efficient and involve complex hinge structures that facilitate amplified wing movement through thoracic deformation. However, in the field of flapping-wing robots, the replication of thoracic skeletal structures has received little attention. In this study, we propose and compare two different hinge models inspired by insect flight: an elastic hinge model (EHM) and an axle hinge model (AHM). Both models were fabricated using 3D printing technology using PLA material. The EHM incorporates flexible structures in both the hinge and lateral scutum regions, allowing for deformation-driven wing motion. In contrast, the AHM employs metal pins in the hinge region to reproduce joint-like articulation, while still permitting elastic deformation in the lateral scutum. To evaluate their performance, we employed an SMA actuator to generate flapping motion, and measured the wing displacement, flapping frequency, and exoskeletal deformation. The experimental results demonstrate that the EHM achieves wing flapping through overall structural flexibility, whereas the AHM provides more defined hinge motion while maintaining exoskeletal elasticity. These findings contribute to our understanding of the role of hinge mechanics in bioinspired flapping-wing robots. Future research will focus on optimizing these mechanisms for higher frequency operation, weight reduction, and better energy efficiency. Full article

(This article belongs to the Special Issue Bioinspired Flapping Wing Aerodynamics: Progress and Challenges)

► Show Figures

Figure 1

30 pages, 5468 KiB

Open AccessArticle

Modified Sparrow Search Algorithm by Incorporating Multi-Strategy for Solving Mathematical Optimization Problems

by Yunpeng Ma, Wanting Meng, Xiaolu Wang, Peng Gu and Xinxin Zhang

Biomimetics 2025, 10(5), 299; https://doi.org/10.3390/biomimetics10050299 - 8 May 2025

Abstract

The Sparrow Search Algorithm (SSA), proposed by Jiankai Xue in 2020, is a swarm intelligence optimization algorithm that has received extensive attention due to its powerful optimization-seeking ability and rapid convergence. However, similar to other swarm intelligence algorithms, the SSA has the problem [...] Read more.

The Sparrow Search Algorithm (SSA), proposed by Jiankai Xue in 2020, is a swarm intelligence optimization algorithm that has received extensive attention due to its powerful optimization-seeking ability and rapid convergence. However, similar to other swarm intelligence algorithms, the SSA has the problem of being prone to falling into local optimal solutions during the optimization process, which limits its application effectiveness. To overcome this limitation, this paper proposes a Modified Sparrow Search Algorithm (MSSA), which enhances the algorithm’s performance by integrating three optimization strategies. Specifically, the Latin Hypercube Sampling (LHS) method is employed to achieve a uniform distribution of the initial population, laying a solid foundation for global search. An adaptive weighting mechanism is introduced in the producer update phase to dynamically adjust the search step size, effectively reducing the risk of the algorithm falling into local optima in later iterations. Meanwhile, the cat mapping perturbation and Cauchy mutation operations are integrated to further enhance the algorithm’s global exploration ability and local development efficiency, accelerating the convergence process and improving the quality of the solutions. This study systematically validates the performance of the MSSA through multi-dimensional experiments. The MSSA demonstrates excellent optimization performance on 23 benchmark test functions and the CEC2019 standard test function set. Its application to three practical engineering problems, namely the design of welded beams, reducers, and cantilever beams, successfully verifies the effectiveness of the algorithm in real-world scenarios. By comparing it with deterministic algorithms such as DIRET and BIRMIN, and based on the five-dimensional test functions generated by the GKLS generator, the global optimization ability of the MSSA is thoroughly evaluated. In addition, the successful application of the MSSA to the problem of robot path planning further highlights its application advantages in complex practical scenarios. Experimental results show that, compared with the original SSA, the MSSA has achieved significant improvements in terms of convergence speed, optimization accuracy, and robustness, providing new ideas and methods for the research and practical application of swarm intelligence optimization algorithms. Full article

► Show Figures

Figure 1

23 pages, 5262 KiB

Open AccessReview

Directional Liquid Transport on Biomimetic Surface with Wedge-Shaped Pattern: Mechanism, Construction, and Applications

by Qing’an Meng, Junjie Zhou, Jie Pang, Luofeng Wang, Kaicheng Yang, Zhangcan Li and Jiayu Xie

Biomimetics 2025, 10(5), 298; https://doi.org/10.3390/biomimetics10050298 - 8 May 2025

Abstract

Natural organisms have evolved highly sophisticated mechanisms for managing water across a broad range of environmental conditions, from arid to highly humid regions. Among these mechanisms, directional liquid transport (DLT) is particularly noteworthy, as it relies on structural designs that facilitate the spontaneous [...] Read more.

Natural organisms have evolved highly sophisticated mechanisms for managing water across a broad range of environmental conditions, from arid to highly humid regions. Among these mechanisms, directional liquid transport (DLT) is particularly noteworthy, as it relies on structural designs that facilitate the spontaneous movement of liquids along predefined pathways without the need for external energy sources. The increasing interest in DLT systems is primarily driven by their potential applications in fields such as microfluidics, water harvesting, and biomedical engineering. The focus on DLT is motivated by its ability to inspire efficient, energy-independent liquid transport technologies, which hold significant promise for both fundamental research and practical applications. Notably, wedge-shaped DLT systems have emerged as a particularly promising area of study due to their advantages in terms of manufacturability, liquid collection efficiency, and scalability—attributes that are essential for industrial deployment. This review seeks to explore natural wedge-based DLT systems, providing an in-depth analysis of their underlying principles and their potential for engineering replication. The discussion includes examples from nature, such as desert beetles and spider silk, and explores the theoretical mechanisms governing these systems, including the role of surface energy gradients and Laplace pressure. Additionally, the review highlights advanced fabrication techniques, such as photolithography and laser micromachining, which are crucial for the development of these systems in practical applications. Full article

► Show Figures

Figure 1

12 pages, 2351 KiB

Open AccessArticle

Effects of Extrusion Pressure During 3D Printing on Viability of Human Bronchial Epithelial Cells in 3D Printed Samples

by Taieba Tuba Rahman, Nathan Wood, Zhijian Pei, Hongmin Qin and Padmini Mohan

Biomimetics 2025, 10(5), 297; https://doi.org/10.3390/biomimetics10050297 - 8 May 2025

Abstract

This study investigates how different levels of extrusion pressure during 3D printing affect the cell viability of human bronchial epithelial (HBE) cells embedded in printed samples. In this study, samples were printed at three levels of extrusion pressure. The cell viability was assessed [...] Read more.

This study investigates how different levels of extrusion pressure during 3D printing affect the cell viability of human bronchial epithelial (HBE) cells embedded in printed samples. In this study, samples were printed at three levels of extrusion pressure. The cell viability was assessed through live/dead staining via microscopic imaging. The results show that increasing the extrusion pressure from 50 to 100 kPa led to a higher degree of cell death. These results demonstrate how the extrusion pressure affects the viability of HBE cells and provide a basis for future studies on pressure-induced responses in respiratory tissues. Full article

(This article belongs to the Special Issue 3D Bio-Printing for Regenerative Medicine Applications)

► Show Figures

Figure 1

19 pages, 844 KiB

Open AccessArticle

Optimizing Class Imbalance in Facial Expression Recognition Using Dynamic Intra-Class Clustering

by Qingdu Li, Keting Fu, Jian Liu, Yishan Li, Qinze Ren, Kang Xu, Junxiu Fu, Na Liu and Ye Yuan

Biomimetics 2025, 10(5), 296; https://doi.org/10.3390/biomimetics10050296 - 8 May 2025

Abstract

While deep neural networks demonstrate robust performance in visual tasks, the long-tail distribution of real-world data leads to significant recognition accuracy degradation in critical scenarios such as medical human–robot affective interaction, particularly the misidentification of low-frequency negative emotions (e.g., fear and disgust) that [...] Read more.

While deep neural networks demonstrate robust performance in visual tasks, the long-tail distribution of real-world data leads to significant recognition accuracy degradation in critical scenarios such as medical human–robot affective interaction, particularly the misidentification of low-frequency negative emotions (e.g., fear and disgust) that may trigger psychological resistance in patients. Here, we propose a method based on dynamic intra-class clustering (DICC) to optimize the class imbalance problem in facial expression recognition tasks. The DICC method dynamically adjusts the distribution of majority classes by clustering them into subclasses and generating pseudo-labels, which helps the model learn more discriminative features and improve classification accuracy. By comparing with existing methods, we demonstrate that the DICC method can help the model achieve superior performance across various facial expression datasets. In this study, we conducted an in-depth evaluation of the DICC method against baseline methods using the FER2013, MMAFEDB, and Emotion-Domestic datasets, achieving improvements in classification accuracy of 1.73%, 1.97%, and 5.48%, respectively. This indicates that the DICC method can effectively enhance classification precision, especially in the recognition of minority class samples. This approach provides a novel perspective for addressing the class imbalance challenge in facial expression recognition and offers a reference for future research and applications in related fields. Full article

(This article belongs to the Special Issue New Biomimetic Advances in Signal and Image Processing for Biomedical Applications 2025)

► Show Figures

Figure 1

27 pages, 2715 KiB

Open AccessReview

A Narrative Review and Clinical Study on Er:YAG Laser Debonding of Ceramic and Composite Veneers

by Jose Villalobos-Tinoco, Fabio Andretti, Clint Conner, Silvia Rojas-Rueda, Nicholas G. Fischer, Margiezel Pagan-Banchs and Carlos A. Jurado

Biomimetics 2025, 10(5), 295; https://doi.org/10.3390/biomimetics10050295 - 6 May 2025

Abstract

Background: Composite resin veneers have gained popularity due to their affordability and minimally invasive application as biomimetic restorations. However, long-term clinical challenges, such as discoloration, wear, and reduced fracture resistance, necessitate their replacement over time. Ceramic veneers, particularly feldspathic and lithium disilicate, offer [...] Read more.

Background: Composite resin veneers have gained popularity due to their affordability and minimally invasive application as biomimetic restorations. However, long-term clinical challenges, such as discoloration, wear, and reduced fracture resistance, necessitate their replacement over time. Ceramic veneers, particularly feldspathic and lithium disilicate, offer superior esthetics and durability, as demonstrated by studies showing their high survival rates and enamel-preserving preparation designs. However, while ceramic veneers survive longer than composite resin veneers, ceramic veneers may need to be removed and replaced. Reports vary for using Er:YAG (erbium-doped yttrium aluminum garnet) lasers for the removal of existing veneers. Methods: A review was conducted to evaluate the effectiveness of removing restorative materials with an Er:YAG laser. A clinical study was included, highlighting the conservative removal of aged composite resin veneers using the Er:YAG laser. This method minimizes enamel damage and facilitates efficient debonding. Following laser application, minimally invasive tooth preparation was performed, and feldspathic porcelain veneers were bonded. Results: The review showed positive outcomes whenever the Er:YAG laser was used. In the case study, after a 3-year follow-up, the restorations exhibited optimal function and esthetics. Conclusions: Laser-assisted debonding provides a safe and predictable method for replacing failing composite veneers with ceramic alternatives, aligning with contemporary biomimetic principles. Full article

(This article belongs to the Special Issue Advances in Biogenic and Biomimetic Materials: From Bionanomedicine to Environmental Applications and Beyond)

► Show Figures

Graphical abstract

20 pages, 9590 KiB

Open AccessArticle

Data-Based Modeling and Control of a Single Link Soft Robotic Arm

by David Abraham Morales-Enríquez, Jaime Guzmán-López, Raúl Alejandro Aguilar-Ramírez, Jorge Luis Lorenzo-Martínez, Daniel Sapién-Garza, Ricardo Cortez, Norma Lozada-Castillo and Alberto Luviano-Juárez

Biomimetics 2025, 10(5), 294; https://doi.org/10.3390/biomimetics10050294 - 6 May 2025

Abstract

In this work, the position control of a cable-driven soft robot is proposed through the approximation of its kinematic model. This approximation is derived from artificial learning rules via neural networks and experimentally observed data. To improve the learning process, a combination of [...] Read more.

In this work, the position control of a cable-driven soft robot is proposed through the approximation of its kinematic model. This approximation is derived from artificial learning rules via neural networks and experimentally observed data. To improve the learning process, a combination of active sampling and Model Agnostic Meta Learning is carried out to improve the data based model to be used in the control stage through the inverse velocity kinematics derived from the data based modeling along with a self differentiation procedure to come up with the pseudo inverse of the robot Jacobian. The proposal is verified in a designed and constructed cable-driven soft robot with three actuators and position measurement through a vision system with three-dimensional motion. Some preliminary assessments (tension and repeatability) were performed to validate the robot movement generation, and, finally, a 3D reference trajectory was tracked using the proposed approach, achieving competitive tracking errors. Full article

(This article belongs to the Special Issue Advancements in Bio-Inspired Soft Robots and Adaptive Mechanisms: Materials, Design and Applications)

► Show Figures

Figure 1

18 pages, 18493 KiB

Open AccessArticle

Modular Snake-like Robot Designed for On-Site Reconfiguration in Space Exploration

by Ning Zhao, Sikai Zhao, Tianjiao Zheng, Jian Qi, Zhiyuan Yang, Xin Sui, Kai Han, Hang Luo, Nanlin Zhou, Jie Zhao and Yanhe Zhu

Biomimetics 2025, 10(5), 293; https://doi.org/10.3390/biomimetics10050293 - 6 May 2025

Abstract

Research on modular robots for space exploration has primarily focused on reconfiguration, with limited attention given to the maneuverability in space environment, which is essential for harnessing the advantages of reconfiguration. In this paper, a modular snake-like robot (MSR) is designed, which is [...] Read more.

Research on modular robots for space exploration has primarily focused on reconfiguration, with limited attention given to the maneuverability in space environment, which is essential for harnessing the advantages of reconfiguration. In this paper, a modular snake-like robot (MSR) is designed, which is expected to emulate a snake to navigate complex environments and employ the reconfiguration capability for on-site shape-shifting. To this end, a snake-like motion analysis and planning method is proposed for MSR. Firstly, we explore the feasibility of utilizing modules in realizing snake-like motion, including functional compatibility and structural constraints. Secondly, we analyze the kinematics of MSR and design joint coordination motion schemes to meet the requirements of snake-like motion. Finally, a path planning method based on reinforcement learning is proposed, which fully considers the motion characteristics and the structural constraints. Through motion analysis and planning, a balance between environmental adaptability and versatility can be achieved. Simulations of comparisons and potential applications further demonstrate the significant advantages of MSR in space exploration. Full article

(This article belongs to the Section Locomotion and Bioinspired Robotics)

► Show Figures

Figure 1

14 pages, 4123 KiB

Open AccessArticle

Research on the Impact Toughness of 3D-Printed CoCrMo Alloy Components Based on Fractal Theory

by Guoqing Zhang, Junxin Li, Han Wang, Congcong Shangguan, Juanjuan Xie and Yongsheng Zhou

Biomimetics 2025, 10(5), 292; https://doi.org/10.3390/biomimetics10050292 - 6 May 2025

Abstract

In order to obtain high-performance 3D printed parts, this study focuses on the key performance indicator of impact toughness. The parametric modeling software Rhino 6 is used to design impact specimens, and the laser selective melting equipment DiMetal-100, independently developed by the South [...] Read more.

In order to obtain high-performance 3D printed parts, this study focuses on the key performance indicator of impact toughness. The parametric modeling software Rhino 6 is used to design impact specimens, and the laser selective melting equipment DiMetal-100, independently developed by the South China University of Technology, is used to manufacture impact specimens. Subsequently, the CoCrMo alloy parts were annealed using an MXQ1600-40 box-type atmosphere furnace and subjected to impact testing using a cantilever beam impact testing machine XJV-22. Fractal theory was applied to analyze the fractal behavior of the resulting impact fracture surfaces. The research results indicate that the 3D-printed impact specimens exhibited excellent surface quality, characterized by brightness, low roughness, and the absence of significant defects such as warping or deformation. In terms of annealing treatment, lower annealing temperatures did not improve the impact performance of SLM-formed CoCrMo alloy parts but instead led to a decrease in toughness. While increasing the annealing temperature can improve toughness to some extent, the effect is limited. Furthermore, the relationship between impact energy and heat treatment temperature exhibits a U-shaped trend. The fractal dimension analysis shows that the parts annealed in a 1200 °C furnace have the highest fractal dimension and better toughness performance. This study introduces a novel approach by comprehensively integrating advanced 3D printing technology, annealing processes, and fractal theory analysis to systematically investigate the influence of annealing temperature on the impact properties of 3D-printed CoCrMo alloy parts, thereby establishing a solid foundation for the application of high-performance 3D printed parts. Full article

(This article belongs to the Special Issue Advances in Bio-Inspired Design and Characterization of 3D-Printed Multimaterial Composites and Heterogeneous Structures)

► Show Figures

Figure 1

16 pages, 4867 KiB

Open AccessArticle

Characterization of Muscle Fatigue Degree in Cyclical Movements Based on the High-Frequency Components of sEMG

by Kexiang Li, Ye Sun, Jiayi Li, Hui Li, Jianhua Zhang and Li Wang

Biomimetics 2025, 10(5), 291; https://doi.org/10.3390/biomimetics10050291 - 6 May 2025

Abstract

Prolonged and high-intensity human–robot interaction can cause muscle fatigue. This fatigue leads to changes in both the time domain and frequency domain of the surface electromyography (sEMG) signals, which are closely related to human body movements. Consequently, these changes affect the accuracy and [...] Read more.

Prolonged and high-intensity human–robot interaction can cause muscle fatigue. This fatigue leads to changes in both the time domain and frequency domain of the surface electromyography (sEMG) signals, which are closely related to human body movements. Consequently, these changes affect the accuracy and stability of using sEMG signals to recognize human body movements. Although numerous studies have confirmed that the median frequency of sEMG signals decreases as the degree of muscle fatigue increases—and this has been used for classifying fatigue and non-fatigue states— there is still a lack of quantitative characterization of the degree of muscle fatigue. Therefore, this paper proposes a method for quantitatively characterizing the degree of muscle fatigue during periodic exercise, based on the high-frequency components obtained through ensemble empirical mode decomposition (EEMD). Firstly, the sEMG signals of the estimated individuals are subjected to EEMD to obtain the high-frequency components, and the short-time Fourier transform is used to calculate the median frequency (MF) of these high-frequency components. Secondly, the obtained median frequencies are linearly fitted, and based on this, a standardized median frequency distribution range (SMFDR) of sEMG signals under muscle fatigue is established. Finally, a muscle fatigue estimator is proposed to achieve the quantification of the degree of muscle fatigue based on the SMFDR. Experimental validation across five subjects demonstrated that this method effectively quantifies cyclical muscle fatigue, with results revealing the methodology exhibits superiority in identifying multiple fatigue states during cyclical movements under consistent loading conditions. Full article

(This article belongs to the Special Issue Computational Biology Simulation, Agent-Based Modelling and AI)

► Show Figures

Figure 1

Journal Description

Biomimetics

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Further Information

Guidelines

MDPI Initiatives

Follow MDPI